Track-to-track Fusion using Multiple Detection Linear Multitarget Integrated Probabilistic Data Association

Yuan Huang, Sa Yong Chong, Taek Lyul Song

Abstract

The multi-sensor multiple detection target tracking problem is considered in this paper. The probability of target existence is used as the track quality measure and plays an important part in the fusion paradigm. The multiple detection linear multi-target integrated probabilistic data association (MD-LM-IPDA) is utilized and extended to the multi-sensor structure. Both centralized fusion MD-LM-IPDA and distributed track-to-track fusion MD-LM-IPDA are proposed. The centralized fusion method utilizes the information from all local sensors' measurements to get the best tracking performance but suffers from the high communication load. The distributed fusion method can control the communication load by adjusting the threshold for transmitting local tracks to the fusion center. One can make a choice between these two structures based on the tracking performance requirement and the computation resources.

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Paper Citation


in Harvard Style

Huang Y., Chong S. and Song T. (2017). Track-to-track Fusion using Multiple Detection Linear Multitarget Integrated Probabilistic Data Association . In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-263-9, pages 431-439. DOI: 10.5220/0006410104310439


in Bibtex Style

@conference{icinco17,
author={Yuan Huang and Sa Yong Chong and Taek Lyul Song},
title={Track-to-track Fusion using Multiple Detection Linear Multitarget Integrated Probabilistic Data Association},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2017},
pages={431-439},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006410104310439},
isbn={978-989-758-263-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Track-to-track Fusion using Multiple Detection Linear Multitarget Integrated Probabilistic Data Association
SN - 978-989-758-263-9
AU - Huang Y.
AU - Chong S.
AU - Song T.
PY - 2017
SP - 431
EP - 439
DO - 10.5220/0006410104310439